| Academic Year |
2026Year |
School/Graduate School |
School of Informatics and Data Science |
| Lecture Code |
KA240501 |
Subject Classification |
Specialized Education |
| Subject Name |
IoT概論 |
Subject Name
（Katakana） |
アイオーティーガイロン |
Subject Name in
English |
Introduction to IoT |
| Instructor |
LI MENGMOU |
Instructor
(Katakana) |
リ メンモ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
3rd-Year, Second Semester, 4Term |
| Days, Periods, and Classrooms |
(4T) Mon5-8：ECON B257 |
| Lesson Style |
Lecture/Seminar |
Lesson Style
(More Details) |
Face-to-face |
| Lecture and hands-on exercises |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
B
:
Japanese／English |
| Course Level |
3
:
Undergraduate High-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
|
| Keywords |
IoTs, embedded system, sensor, wireless communication, smart devices, Linux, Python |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Computer Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
Data Science Program
（Abilities and Skills）
・A. Information infrastructure development technology, information processing technology, technology that analyzes data and creates new added value.
Intelligence Science Program
（Abilities and Skills）
・D2. Information processing ability and data analysis ability to contribute to the application and development of artificial intelligence and IoT.
（Comprehensive Abilities）
・D3. Ability to grasp complexly intertwined social needs and issues from a bird's-eye view and solve issues with a multifaceted perspective and analytical ability based on a wide range of knowledge in intelligent science. |
|---|
Class Objectives
/Class Outline |
The aim is to introduce students to the fundamentals of IoT technology and applications, laying the groundwork for future related research and projects. |
| Class Schedule |
lesson1 Introduction to IoT systems Lecture
lesson2 Introduction to IoT systems Exercises
lesson3 IoT Components & Basic Embedded Programming Lecture
lesson4 IoT Components & Basic Embedded Programming Exercises
lesson5 Communication Protocols & Networking Basics Lecture
lesson6 Communication Protocols & Networking Basics Exercises
lesson7 Data Processing & Cloud Integration Lecture
lesson8 Data Processing & Cloud Integration Exercises
lesson9 IoT Security & Privacy Lecture
lesson10 IoT Security & Privacy Exercises
lesson11 IoT Data Pipeline Lecture
lesson12 IoT Data Pipeline Exercises
lesson13 IoT and Machine Learning Lecture
lesson14 IoT and Machine Learning Exercises
lesson15
Final report is required. |
Text/Reference
Books,etc. |
References will be distributed. |
PC or AV used in
Class,etc. |
Text, Handouts, Microsoft Teams, moodle |
| (More Details) |
|
| Learning techniques to be incorporated |
Discussions, Paired Reading, Project Learning, Post-class Report |
Suggestions on
Preparation and
Review |
It is recommended to have basic knowledge of C/C++ and Python. |
| Requirements |
|
| Grading Method |
Final grade will be based on participation in clase(14%), exercises(35%), final project(30%) and report(21%). |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |